Comparison of five different popular scoring systems to predict nonsentinel lymph node status in patients with metastatic sentinel lymph nodes: a tertiary care center experience
Identifieur interne : 001F87 ( Main/Merge ); précédent : 001F86; suivant : 001F88Comparison of five different popular scoring systems to predict nonsentinel lymph node status in patients with metastatic sentinel lymph nodes: a tertiary care center experience
Auteurs : Ramazan Y Ld Z [Turquie] ; Murat Urkan [Turquie] ; O Uz Hancerliogullar [Turquie] ; Zafer K Lba [Turquie] ; Erkan Ozturk [Turquie] ; Mustafa Oner Mentes [Turquie] ; Semih Gorgulu [Turquie]Source :
- SpringerPlus [ 2193-1801 ] ; 2015.
Abstract
Sentinel lymph node biopsy (SLNB) is the current standard of care for breast cancers with no clinically palpable axillary lymph nodes. Almost 50 % of sentinel lymph node positive patients have negative non-sentinel nodes and undergo non-therapeutic axillary dissection. Five different scoring systems, reported in the literature, were compared for their predictive ability of non-SLN involvement in patients with SLN positive breast cancer. 242 patients who underwent breast surgery and SLNB were included in the study. Of these, 70 who were confirmed to have SLN metastasis and received complementary ALND and constituted the final study population. The nomograms (MSKCC, M.D. Anderson Cancer Center, Tenon model, Stanford and Turkish) were statistically compared for their prediction of non-SLN metastasis (95 % confidence interval). We have determined only two clinicopathologic (multifocality and size of the primary tumor) situations which have a statistically significant association between SLN metastasis with using a multivariate logistic regression analysis. Multifocality (P = 0.001) and size of the primary tumor (P = 0.001) were associated with a higher probability of-SLN metastasis. No predictive model was constructed that showed good area under the curve (AUC) discrimination in the validation series. Currently published predictive models lack accuracy when applied to a different population. Multi-institutional heterogenic population studies are important to determine the exact combination of scoring systems and/or nomograms.
Url:
DOI: 10.1186/s40064-015-1442-4
PubMed: 26543785
PubMed Central: 4628030
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type="doi">10.1186/s40064-015-1442-4</idno><date when="2015">2015</date><idno type="wicri:Area/Pmc/Corpus">000E56</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000E56</idno><idno type="wicri:Area/Pmc/Curation">000E55</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000E55</idno><idno type="wicri:Area/Pmc/Checkpoint">001397</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">001397</idno><idno type="wicri:Area/Ncbi/Merge">007B08</idno><idno type="wicri:Area/Ncbi/Curation">007B08</idno><idno type="wicri:Area/Ncbi/Checkpoint">007B08</idno><idno type="wicri:Area/Main/Merge">001F87</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Comparison of five different popular scoring systems to predict nonsentinel lymph node status in patients with metastatic sentinel lymph nodes: a tertiary care center experience</title><author><name sortKey="Y Ld Z, Ramazan" sort="Y Ld Z, Ramazan" uniqKey="Y Ld Z R" first="Ramazan" last="Y Ld Z">Ramazan Y Ld Z</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara, Turkey</nlm:aff><country xml:lang="fr">Turquie</country><wicri:regionArea>Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara</wicri:regionArea><wicri:noRegion>06018 Ankara</wicri:noRegion></affiliation></author><author><name sortKey="Urkan, Murat" sort="Urkan, Murat" uniqKey="Urkan M" first="Murat" last="Urkan">Murat Urkan</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara, Turkey</nlm:aff><country xml:lang="fr">Turquie</country><wicri:regionArea>Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara</wicri:regionArea><wicri:noRegion>06018 Ankara</wicri:noRegion></affiliation></author><author><name sortKey="Hancerliogullar, O Uz" sort="Hancerliogullar, O Uz" uniqKey="Hancerliogullar O" first="O Uz" last="Hancerliogullar">O Uz Hancerliogullar</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara, Turkey</nlm:aff><country xml:lang="fr">Turquie</country><wicri:regionArea>Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara</wicri:regionArea><wicri:noRegion>06018 Ankara</wicri:noRegion></affiliation></author><author><name sortKey="K Lba, Zafer" sort="K Lba, Zafer" uniqKey="K Lba Z" first="Zafer" last="K Lba">Zafer K Lba</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara, Turkey</nlm:aff><country xml:lang="fr">Turquie</country><wicri:regionArea>Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara</wicri:regionArea><wicri:noRegion>06018 Ankara</wicri:noRegion></affiliation></author><author><name sortKey="Ozturk, Erkan" sort="Ozturk, Erkan" uniqKey="Ozturk E" first="Erkan" last="Ozturk">Erkan Ozturk</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara, Turkey</nlm:aff><country xml:lang="fr">Turquie</country><wicri:regionArea>Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara</wicri:regionArea><wicri:noRegion>06018 Ankara</wicri:noRegion></affiliation></author><author><name sortKey="Mentes, Mustafa Oner" sort="Mentes, Mustafa Oner" uniqKey="Mentes M" first="Mustafa Oner" last="Mentes">Mustafa Oner Mentes</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara, Turkey</nlm:aff><country xml:lang="fr">Turquie</country><wicri:regionArea>Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara</wicri:regionArea><wicri:noRegion>06018 Ankara</wicri:noRegion></affiliation></author><author><name sortKey="Gorgulu, Semih" sort="Gorgulu, Semih" uniqKey="Gorgulu S" first="Semih" last="Gorgulu">Semih Gorgulu</name><affiliation wicri:level="1"><nlm:aff id="Aff1">Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara, Turkey</nlm:aff><country xml:lang="fr">Turquie</country><wicri:regionArea>Department of Surgery, Gulhane Military Medical Academy, Etlik, 06018 Ankara</wicri:regionArea><wicri:noRegion>06018 Ankara</wicri:noRegion></affiliation></author></analytic><series><title level="j">SpringerPlus</title><idno type="eISSN">2193-1801</idno><imprint><date when="2015">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Sentinel lymph node biopsy (SLNB) is the current standard of care for breast cancers with no clinically palpable axillary lymph nodes. Almost 50 % of sentinel lymph node positive patients have negative non-sentinel nodes and undergo non-therapeutic axillary dissection. Five different scoring systems, reported in the literature, were compared for their predictive ability of non-SLN involvement in patients with SLN positive breast cancer. 242 patients who underwent breast surgery and SLNB were included in the study. Of these, 70 who were confirmed to have SLN metastasis and received complementary ALND and constituted the final study population. The nomograms (MSKCC, M.D. Anderson Cancer Center, Tenon model, Stanford and Turkish) were statistically compared for their prediction of non-SLN metastasis (95 % confidence interval). We have determined only two clinicopathologic (multifocality and size of the primary tumor) situations which have a statistically significant association between SLN metastasis with using a multivariate logistic regression analysis. Multifocality (P = 0.001) and size of the primary tumor (P = 0.001) were associated with a higher probability of-SLN metastasis. No predictive model
was constructed that showed good area under the curve (AUC) discrimination in the validation series. Currently published predictive models lack accuracy when applied to a different population. Multi-institutional heterogenic population studies are important to determine the exact combination of scoring systems and/or nomograms.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Alran, S" uniqKey="Alran S">S Alran</name></author><author><name sortKey="De, Rycke Y" uniqKey="De R">Rycke Y De</name></author><author><name sortKey="Fourchotte, V" uniqKey="Fourchotte V">V Fourchotte</name></author><author><name sortKey="Charitansky, H" uniqKey="Charitansky H">H Charitansky</name></author><author><name sortKey="Laki, F" uniqKey="Laki F">F Laki</name></author><author><name sortKey="Falcou, Mc" uniqKey="Falcou M">MC Falcou</name></author><author><name sortKey="Benamor, M" uniqKey="Benamor M">M Benamor</name></author><author><name sortKey="Freneaux, P" uniqKey="Freneaux P">P Freneaux</name></author><author><name sortKey="Salmon, Rj" uniqKey="Salmon R">RJ Salmon</name></author><author><name sortKey="Sigal Zafrani, B" uniqKey="Sigal 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